Overview

Dataset statistics

Number of variables6
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory55.6 B

Variable types

Text1
Numeric4
Categorical1

Dataset

Description서울주택도시공사 결산 내역입니다 재무상태표(요약) 과 손익계산서 내역을 표시해주며 결산내역을 확인할 수 있습니다.
Author서울주택도시공사
URLhttps://www.data.go.kr/data/15076115/fileData.do

Alerts

2022년(억) is highly overall correlated with 2021년(억) and 3 other fieldsHigh correlation
2021년(억) is highly overall correlated with 2022년(억) and 2 other fieldsHigh correlation
2020년(억) is highly overall correlated with 2022년(억) and 2 other fieldsHigh correlation
증감(억) is highly overall correlated with 2022년(억)High correlation
비고 is highly overall correlated with 2022년(억) and 2 other fieldsHigh correlation
과목 has unique valuesUnique
증감(억) has 1 (2.7%) zerosZeros

Reproduction

Analysis started2023-12-23 06:48:53.238855
Analysis finished2023-12-23 06:49:03.444055
Duration10.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

과목
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-23T06:49:03.863654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length15
Mean length10.891892
Min length4

Characters and Unicode

Total characters403
Distinct characters72
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row1.유동자산
2nd row1.유동자산 - 당좌자산
3rd row1.유동자산 - 재고자산
4th row2. 비유동자산
5th row2. 비유동자산 - 투자자산
ValueCountFrequency (%)
18
17.8%
2 11
 
10.9%
비유동자산 5
 
5.0%
매출원가 5
 
5.0%
1.매출액 5
 
5.0%
4 4
 
4.0%
1.유동자산 3
 
3.0%
영업이익 3
 
3.0%
3 3
 
3.0%
분양택지 2
 
2.0%
Other values (35) 42
41.6%
2023-12-23T06:49:05.325747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64
 
15.9%
. 33
 
8.2%
자 22
 
5.5%
- 18
 
4.5%
산 17
 
4.2%
매 13
 
3.2%
익 12
 
3.0%
유 12
 
3.0%
출 12
 
3.0%
2 12
 
3.0%
Other values (62) 188
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 255
63.3%
Space Separator 64
 
15.9%
Other Punctuation 33
 
8.2%
Decimal Number 33
 
8.2%
Dash Punctuation 18
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
자 22
 
8.6%
산 17
 
6.7%
매 13
 
5.1%
익 12
 
4.7%
유 12
 
4.7%
출 12
 
4.7%
동 11
 
4.3%
업 11
 
4.3%
비 11
 
4.3%
이 10
 
3.9%
Other values (52) 124
48.6%
Decimal Number
ValueCountFrequency (%)
2 12
36.4%
1 10
30.3%
4 4
 
12.1%
3 3
 
9.1%
6 2
 
6.1%
5 1
 
3.0%
7 1
 
3.0%
Space Separator
ValueCountFrequency (%)
64
100.0%
Other Punctuation
ValueCountFrequency (%)
. 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 255
63.3%
Common 148
36.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
자 22
 
8.6%
산 17
 
6.7%
매 13
 
5.1%
익 12
 
4.7%
유 12
 
4.7%
출 12
 
4.7%
동 11
 
4.3%
업 11
 
4.3%
비 11
 
4.3%
이 10
 
3.9%
Other values (52) 124
48.6%
Common
ValueCountFrequency (%)
64
43.2%
. 33
22.3%
- 18
 
12.2%
2 12
 
8.1%
1 10
 
6.8%
4 4
 
2.7%
3 3
 
2.0%
6 2
 
1.4%
5 1
 
0.7%
7 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 255
63.3%
ASCII 148
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64
43.2%
. 33
22.3%
- 18
 
12.2%
2 12
 
8.1%
1 10
 
6.8%
4 4
 
2.7%
3 3
 
2.0%
6 2
 
1.4%
5 1
 
0.7%
7 1
 
0.7%
Hangul
ValueCountFrequency (%)
자 22
 
8.6%
산 17
 
6.7%
매 13
 
5.1%
익 12
 
4.7%
유 12
 
4.7%
출 12
 
4.7%
동 11
 
4.3%
업 11
 
4.3%
비 11
 
4.3%
이 10
 
3.9%
Other values (52) 124
48.6%

2022년(억)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47674.784
Minimum-90
Maximum279625
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)5.4%
Memory size465.0 B
2023-12-23T06:49:06.118996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-90
5-th percentile62.4
Q11427
median5772
Q335218
95-th percentile229453
Maximum279625
Range279715
Interquartile range (IQR)33791

Descriptive statistics

Standard deviation81501.778
Coefficient of variation (CV)1.7095364
Kurtosis2.4512479
Mean47674.784
Median Absolute Deviation (MAD)5788
Skewness1.8955304
Sum1763967
Variance6.6425398 × 109
MonotonicityNot monotonic
2023-12-23T06:49:06.786488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
2556 2
 
5.4%
279625 2
 
5.4%
62715 1
 
2.7%
3235 1
 
2.7%
128 1
 
2.7%
15900 1
 
2.7%
514 1
 
2.7%
9532 1
 
2.7%
5772 1
 
2.7%
82 1
 
2.7%
Other values (25) 25
67.6%
ValueCountFrequency (%)
-90 1
2.7%
-16 1
2.7%
82 1
2.7%
128 1
2.7%
180 1
2.7%
249 1
2.7%
514 1
2.7%
582 1
2.7%
937 1
2.7%
1427 1
2.7%
ValueCountFrequency (%)
279625 2
5.4%
216910 1
2.7%
199645 1
2.7%
181687 1
2.7%
152838 1
2.7%
97938 1
2.7%
72982 1
2.7%
62715 1
2.7%
35218 1
2.7%
28849 1
2.7%

2021년(억)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46894.297
Minimum-82
Maximum271481
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)5.4%
Memory size465.0 B
2023-12-23T06:49:07.712368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-82
5-th percentile43.2
Q11398
median8788
Q335796
95-th percentile217069.8
Maximum271481
Range271563
Interquartile range (IQR)34398

Descriptive statistics

Standard deviation77765.795
Coefficient of variation (CV)1.6583209
Kurtosis2.5793025
Mean46894.297
Median Absolute Deviation (MAD)8721
Skewness1.9008333
Sum1735089
Variance6.0475188 × 109
MonotonicityNot monotonic
2023-12-23T06:49:08.683263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1879 2
 
5.4%
271481 2
 
5.4%
68014 1
 
2.7%
2798 1
 
2.7%
67 1
 
2.7%
22130 1
 
2.7%
7088 1
 
2.7%
8788 1
 
2.7%
6196 1
 
2.7%
58 1
 
2.7%
Other values (25) 25
67.6%
ValueCountFrequency (%)
-82 1
2.7%
-16 1
2.7%
58 1
2.7%
67 1
2.7%
140 1
2.7%
283 1
2.7%
481 1
2.7%
571 1
2.7%
1207 1
2.7%
1398 1
2.7%
ValueCountFrequency (%)
271481 2
5.4%
203467 1
2.7%
186411 1
2.7%
176341 1
2.7%
140545 1
2.7%
95140 1
2.7%
71195 1
2.7%
68014 1
2.7%
35796 1
2.7%
34313 1
2.7%

2020년(억)
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45906.054
Minimum-62
Maximum266239
Zeros0
Zeros (%)0.0%
Negative2
Negative (%)5.4%
Memory size465.0 B
2023-12-23T06:49:09.607290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-62
5-th percentile20.4
Q11379
median7806
Q352967
95-th percentile205074.2
Maximum266239
Range266301
Interquartile range (IQR)51588

Descriptive statistics

Standard deviation75006.85
Coefficient of variation (CV)1.6339206
Kurtosis2.7595524
Mean45906.054
Median Absolute Deviation (MAD)7763
Skewness1.91064
Sum1698524
Variance5.6260275 × 109
MonotonicityNot monotonic
2023-12-23T06:49:11.063570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1781 2
 
5.4%
266239 2
 
5.4%
76456 1
 
2.7%
2835 1
 
2.7%
43 1
 
2.7%
20771 1
 
2.7%
7806 1
 
2.7%
7223 1
 
2.7%
5713 1
 
2.7%
29 1
 
2.7%
Other values (25) 25
67.6%
ValueCountFrequency (%)
-62 1
2.7%
-14 1
2.7%
29 1
2.7%
43 1
2.7%
46 1
2.7%
467 1
2.7%
499 1
2.7%
824 1
2.7%
1314 1
2.7%
1379 1
2.7%
ValueCountFrequency (%)
266239 2
5.4%
189783 1
2.7%
175299 1
2.7%
174530 1
2.7%
122332 1
2.7%
90940 1
2.7%
76456 1
2.7%
67871 1
2.7%
52967 1
2.7%
42535 1
2.7%

증감(억)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean780.48649
Minimum-10351
Maximum13443
Zeros1
Zeros (%)2.7%
Negative10
Negative (%)27.0%
Memory size465.0 B
2023-12-23T06:49:11.883714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-10351
5-th percentile-6648.6
Q1-8
median317
Q31019
95-th percentile12481.2
Maximum13443
Range23794
Interquartile range (IQR)1027

Descriptive statistics

Standard deviation5317.458
Coefficient of variation (CV)6.8130046
Kurtosis0.98936964
Mean780.48649
Median Absolute Deviation (MAD)598
Skewness0.58499487
Sum28878
Variance28275360
MonotonicityNot monotonic
2023-12-23T06:49:12.681932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
677 2
 
5.4%
8144 2
 
5.4%
-5299 1
 
2.7%
437 1
 
2.7%
61 1
 
2.7%
-6230 1
 
2.7%
-6574 1
 
2.7%
744 1
 
2.7%
-424 1
 
2.7%
24 1
 
2.7%
Other values (25) 25
67.6%
ValueCountFrequency (%)
-10351 1
2.7%
-6947 1
2.7%
-6574 1
2.7%
-6230 1
2.7%
-6204 1
2.7%
-5793 1
2.7%
-5299 1
2.7%
-424 1
2.7%
-281 1
2.7%
-8 1
2.7%
ValueCountFrequency (%)
13443 1
2.7%
13234 1
2.7%
12293 1
2.7%
8144 2
5.4%
5346 1
2.7%
4295 1
2.7%
2798 1
2.7%
1787 1
2.7%
1019 1
2.7%
905 1
2.7%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
손익계산서
19 
재무상태표 [요약]
18 

Length

Max length10
Median length5
Mean length7.4324324
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row재무상태표 [요약]
2nd row재무상태표 [요약]
3rd row재무상태표 [요약]
4th row재무상태표 [요약]
5th row재무상태표 [요약]

Common Values

ValueCountFrequency (%)
손익계산서 19
51.4%
재무상태표 [요약] 18
48.6%

Length

2023-12-23T06:49:13.273114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-23T06:49:13.794838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
손익계산서 19
34.5%
재무상태표 18
32.7%
요약 18
32.7%

Interactions

2023-12-23T06:48:59.661126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:54.266747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:56.056850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:57.718020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:49:00.221295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:54.672374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:56.396719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:58.178417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:49:00.858132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:54.990555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:56.692299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:58.628553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:49:01.626118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:55.585748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:57.153270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-23T06:48:59.266789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-23T06:49:14.195954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과목2022년(억)2021년(억)2020년(억)증감(억)비고
과목1.0001.0001.0001.0001.0001.000
2022년(억)1.0001.0000.9960.9960.8880.735
2021년(억)1.0000.9961.0001.0000.8660.805
2020년(억)1.0000.9961.0001.0000.8660.805
증감(억)1.0000.8880.8660.8661.0000.363
비고1.0000.7350.8050.8050.3631.000
2023-12-23T06:49:15.067900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2022년(억)2021년(억)2020년(억)증감(억)비고
2022년(억)1.0000.9550.9430.5560.509
2021년(억)0.9551.0000.9980.4380.567
2020년(억)0.9430.9981.0000.4090.567
증감(억)0.5560.4380.4091.0000.347
비고0.5090.5670.5670.3471.000

Missing values

2023-12-23T06:49:02.447876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-23T06:49:03.237572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

과목2022년(억)2021년(억)2020년(억)증감(억)비고
01.유동자산627156801476456-5299재무상태표 [요약]
11.유동자산 - 당좌자산352183431333921905재무상태표 [요약]
21.유동자산 - 재고자산274973370142535-6204재무상태표 [요약]
32. 비유동자산21691020346718978313443재무상태표 [요약]
42. 비유동자산 - 투자자산376240433903-281재무상태표 [요약]
52. 비유동자산 - 유형자산19964518641117453013234재무상태표 [요약]
62. 비유동자산 - 무형자산1801404640재무상태표 [요약]
72. 비유동자산 - 기타비유동자산133231287311304450재무상태표 [요약]
8자산합계2796252714812662398144재무상태표 [요약]
9자산합계1. 유동부채288493579652967-6947재무상태표 [요약]
과목2022년(억)2021년(억)2020년(억)증감(억)비고
272. 매출원가 - 기타사업82582924손익계산서
283. 매출총이익323527982835437손익계산서
293. 매출총이익 - 판매비와 관리비152412071379317손익계산서
304. 영업이익171115911456120손익계산서
314. 영업이익 - 영업외 수익1427571824856손익계산서
324. 영업이익 - 영업외 비용582283499299손익계산서
335. 경상이익255618791781677손익계산서
346. 세전순이익255618791781677손익계산서
356. 세전순이익 - 법인세비용937481467456손익계산서
367. 당기순이익161913981314221손익계산서